byalterlab-ieu· 90 skills
Generate de-novo protein backbones with RFdiffusion (Watson 2023) — a diffusion model for unconditional monomer generation, motif scaffolding, binder design against a target, and symmetric oligomers. Use when generating a new protein backbone from scratch, scaffolding a functional motif into a fold, designing a binder backbone to a target surface, or building symmetric assemblies; RFdiffusion produces the STRUCTURE, then alterlab-proteinmpnn designs its sequence and alterlab-alphafold validates it. For sequence design of an existing backbone prefer alterlab-proteinmpnn (or alterlab-ligandmpnn with a ligand); to fold a known sequence prefer alterlab-alphafold; for generative multimodal design prefer alterlab-esm. Part of the AlterLab Academic Skills suite.
$npx -y skills add alterlab-ieu/alterlab-academic-skills --skill alterlab-rfdiffusionInstalls into the current project.
Run `npx skills use "https://github.com/alterlab-ieu/alterlab-academic-skills" --skill "alterlab-ieu/alterlab-academic-skills/alterlab-rfdiffusion"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/alterlab-ieu/alterlab-academic-skills" that are relevant to the current task. Run `npx skills add "https://github.com/alterlab-ieu/alterlab-academic-skills"` and select the relevant skills, then follow their instructions.